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Primary Data Analysis Method for Comparing Adaptive Interventions

We illustrate the use of a primary data analysis method for comparing adaptive interventions that are embedded in a sequential, multiple assignment, randomized trial (SMART). Here we illustrate the use of the SAS GENMOD procedure to analyze a fake data set similar to the ADHD example described in Nahum-Shani et al. (2010).

A SMART is a multi-stage randomized trial, where each stage corresponds to a critical decision. Each participant progresses through the stages and is randomly assigned to one of several intervention options at each stage (Murphy, 2005). In this context, one type of primary data analysis focuses on addressing research questions concerning the comparison of adaptive interventions that are embedded in the SMART design.

In this example two-stage SMART, participants' responses to the first-stage intervention determine whether they will be re-randomized. In such designs, either responders or non-responders enter the second stage of the intervention while the others remain in the first stage of the intervention. More specifically, in the example in the paper, children with ADHD were randomized at the first stage of the intervention to either low-dose behavioral intervention (coded as 1) or low-dose medication (coded as -1). Non-responders to the first-stage of the intervention were then re-randomized to two second-stage intervention options: either intensifying the same intervention (coded as 1) or augmenting it with the other type of intervention (coded as -1). Responders to the first-stage intervention did not enter the second stage; they continued receiving the first-stage intervention option.